EP3974104A1 - System zur bearbeitungskontrolle eines werkstücks - Google Patents

System zur bearbeitungskontrolle eines werkstücks Download PDF

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Publication number
EP3974104A1
EP3974104A1 EP21188642.9A EP21188642A EP3974104A1 EP 3974104 A1 EP3974104 A1 EP 3974104A1 EP 21188642 A EP21188642 A EP 21188642A EP 3974104 A1 EP3974104 A1 EP 3974104A1
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European Patent Office
Prior art keywords
cutting
angle
parameters
values
parameter
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French (fr)
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EP3974104B1 (de
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Emeric NOIROT-NERIN
Ivan HAMM
Gérard POULACHON
Frédéric ROSSI
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Airbus Operations SAS
Airbus SAS
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Airbus Operations SAS
Airbus SAS
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
    • G05B19/4065—Monitoring tool breakage, life or condition
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/409—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using manual data input [MDI] or by using control panel, e.g. controlling functions with the panel; characterised by control panel details or by setting parameters
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/33—Director till display
    • G05B2219/33258—Common coordinate conversion for multiple heads, spindles
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/37—Measurements
    • G05B2219/37258—Calculate wear from workpiece and tool material, machining operations
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/37—Measurements
    • G05B2219/37355—Cutting, milling, machining force
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/45—Nc applications
    • G05B2219/45044—Cutting
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/50—Machine tool, machine tool null till machine tool work handling
    • G05B2219/50206—Tool monitoring integrated in nc control
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/50—Machine tool, machine tool null till machine tool work handling
    • G05B2219/50319—As function of tool geometry and machining data

Definitions

  • the present invention relates to the field of the machining of a part and in particular, the control of the machining of an avionic part.
  • the ManHIRP project Integrating process controls with Manufacturing to produce High Integrity Rotating Parts for modern gas turbines brought together all European engine manufacturers.
  • the objective of this program was to metallurgically characterize machining defects, to study their detectability during and after machining and to evaluate their fatigue effect in order to measure their severity.
  • the culmination of this study was to obtain the most detrimental anomalies on the fatigue resistance of materials whose defects were most often simulated.
  • the ACCENT project whose primary objective was to show the usefulness of using monitoring means during machining in order to secure the operation with regard to material integrity.
  • These monitoring means could be used as non-destructive testing (NDT) making it possible to detect, quantify or even anticipate material damage during machining.
  • NDT non-destructive testing
  • the second objective of using monitoring means is to be able to adapt the machining process to variations in the manufacturing process (cutting conditions, tool wear, etc.) by validating areas of use and no longer focusing on a fixed procedure.
  • the expected benefits would be significant and relate to the reduction of machining time, the optimization of tool life and the elimination of revalidation costs linked to minor changes in the manufacturing process.
  • Airbus launched the HOMDA (HOlistic Machining Digital Approach) project defining the means of monitoring and automation to increase machining productivity while guaranteeing the material integrity of the part.
  • Specific cutting coefficients vary according to the kinematic machining parameters (cutting speed, tool feed and engagement, etc.), the nature of the machined material (titanium alloy, aluminum, ferrous alloy, etc.), the nature of the material being machined (grade of carbide, ARS, ceramic, etc.) and the geometry of the cutting edge (rake angle, clearance angle, fillet radius, helix angle, etc.).
  • MOCN Machine-Tools with Numerical Controls
  • the MOCNs are very efficient in following the tool paths that have been programmed, but they lack information about the course of the cut. Therefore, without instrumentation, they cannot raise their level of “intelligence” and self-detect failures such as tool or spindle damage, excessive wear, vibration, collision, etc. missing part or tool, etc. It is therefore necessary to instrument the MOCNs in order to acquire information and force signals on the progress of the machining.
  • the force signals contain a great deal of information, in particular regarding the state of the tool and its level of wear. But it is also possible, for an identified thermomechanical load that would be applied to the machined surface, to deduce the cause and effect relationship between the surface integrity and the operating parameters. The force signals then become an index of the quality of the machined surface.
  • the machining power depending on the cutting forces, contains information on the integrity of the couple of machined and machining materials.
  • the power consumed by the spindle is often used (ex.: Artis or DigitalWay systems).
  • the power consumed does not fully have sufficient sensitivity to detect damage to the tool.
  • Force measurements thrust force and tool torque
  • Dynamometric tables are very widely used for measuring cutting forces and are the tool of choice for carrying out experimental research work. Indeed, their high precision, sensitivities and bandwidths make it possible to establish relationships between cutting forces and operating parameters, as well as to validate machining monitoring strategies. However, their cost is high and they can be damaged in the event of an impact. Their dimensions considerably limit the working space (machining of small parts) and specific part holders must be made. For all these reasons, load tables cannot be used industrially, in production.
  • the qualification of the window of operating parameters can be carried out by directly correlating the kinematic parameters with the number of cycles to failure of the machined material. It is therefore a question of machining, under the operating conditions subject to qualification, a statistical sample of several fatigue specimens (Standard EN 6072) by varying the operating kinematic conditions, then testing the lifespan of the samples (Bending test ). The operating conditions for which the samples respond favorably to the life criteria in terms of fatigue are then qualified.
  • the object of the present invention is therefore to propose a system (and a method) taking into account the thermomechanical aspects of the materials to determine in a simple and rapid manner the optimal cutting conditions and to automatically control the machining in order to preserve the integrity of the machined part.
  • This system establishes a window of cutting conditions guaranteeing the material integrity of the machined part. Indeed, the system takes into account the output parameters representative of the material integrity of the machined part to select the appropriate cutting conditions and to control the machining in order to preserve the integrity of the part.
  • said acquisition module is configured to acquire during machining of the part at least one cutting signal
  • said microprocessor is configured to control the progress of the cutting operations by ensuring that the value of said cutting signal is bounded by said fatigue threshold.
  • said at least one cutting operating parameter is a torque parameter C representative of a torque signal from the machining machine or a power parameter representative of a power signal from the machining machine
  • said at least one fatigue threshold is a torque threshold or a power threshold
  • the torque and power signals are very easy to measure, thus making it possible to guarantee the integrity of the machined part simply, quickly and at low cost, knowing that in general machining machines already include sensors for measuring power and of torque.
  • the integrity model makes it possible to correlate surface integrity properties with operating parameters and cutting tools. This makes it possible to frame parameters of cutting conditions and to simulate the loading of such parameters on the surface of the machined part. Thus, from the operating parameters and the cutting tool parameters, the model is able to predict how these parameters will thermo-mechanically load the material. Specifically, the mechanical loading parameters provide information on the interactions between the tool and the part, and therefore on the progress of the machining, on the vibratory behavior, on the state of the tool, that of the spindle and on the material health or surface integrity of the workpiece.
  • the microprocessor is also configured to calculate the specific cutting coefficients comprising a tangential edge force coefficient K tc , a radial edge force coefficient K rc , and an axial edge force coefficient K ac , as a function of the shear stress ⁇ s and the oblique shear angle ⁇ i , the normal shear angle ⁇ n , the normal projection angle ⁇ n , the oblique projection angle ⁇ i and the helix angle ⁇ s .
  • the specific cutting coefficients represent the cutting forces and temperatures that predict the surface integrity of machined materials.
  • the present invention also relates to a numerically controlled machining machine comprising the control system according to any one of the preceding characteristics.
  • the principle of the invention consists in controlling the progress of the cutting operations of a part according to parameters representative of the material integrity of the machined part determined according to the thermomechanical aspects of the part.
  • machining is a manufacturing process by removal of material. Therefore, energetic efforts via mechanical actions are required to plastically deform, separate and remove material from the workpiece.
  • the present invention provides to analyze these mechanical actions to determine the interactions between the tool and the machined part to then control and monitor the material integrity of any part during its machining.
  • the Fig. 1 schematically illustrates a part machining control system, according to one embodiment of the invention.
  • the control system 1 comprises an acquisition module 3, a microprocessor 5, a storage unit 7, an input interface 9 (for example, a keyboard) and an output interface 11 (for example a screen).
  • all of these hardware elements of the control system 1 are already integrated into a control device 13 of a numerically controlled machine 15 .
  • the machining machine 15 is generally equipped with a magazine in which are arranged various cutting tools 17 (boring-drilling machines, milling machines, etc.) making it possible to machine programmed shapes on the part 19 of interest.
  • the acquisition module 3 is configured to acquire data corresponding to a set of input parameters relating to cutting conditions and properties of the material of the part 19 to be machined. These input parameters relate to kinematic, geometric, tribological or physical variables relating to the part to be machined and to the machining tool.
  • the microprocessor 5 is configured to determine at least one operational cutting parameter representative of a cutting signal coming from the machining machine 15 by using a set of output parameters of an integrity model 21 constructed beforehand during a learning phase and stored in the storage unit 7.
  • This integrity model 21 is constructed in such a way as to link the set of input parameters to the set of output parameters which include specific cutting coefficients representative of the material integrity of the machined part (see Fig. 2 ).
  • the microprocessor 5 is configured to establish a fatigue threshold relating to each cutting operating parameter.
  • Each fatigue threshold corresponds to a window of cutting conditions allowing the progress of the cutting operations to be controlled, knowing that the corresponding cutting operating parameter has an influence on the mechanical behavior of the part 19 machined.
  • the control of operations via the cutting conditions window guarantees the material integrity of part 19.
  • the acquisition module 3 is configured to acquire at least one cutting signal during an operating mode for machining the part.
  • the cutting operating parameter can advantageously be a torque parameter C representative of a torque signal from the spindle of the machining machine 15 or a power parameter representative of a power signal from also from the machining machine 15.
  • the corresponding fatigue threshold is a torque threshold or a power threshold.
  • machining machines 15 already include sensors for measuring power and torque. These values depend on the machined material.
  • the power threshold is around 1600 W and the torque threshold is around 60 Nm.
  • the microprocessor 5 is configured to control and monitor in real time the progress of the cutting operations by comparing the value of the fatigue threshold corresponding to the cutting signal and by ensuring that the value of the cutting signal is always limited by fatigue threshold. Thus, the material integrity of the machined part 19 is ensured as long as the cutting signal does not exceed the corresponding fatigue threshold.
  • the power is controlled by the microprocessor to remain between 80 W and 1600 W and likewise the torque is controlled to remain between 8 Nm and 60.
  • the operating cutting parameter can also be the electric current consumed by the machining machine 15 knowing that the latter also includes a current measurement sensor.
  • the cutting operating parameter may be the vibration of the spindle of the machining machine 15 or any other parameter.
  • the Fig. 2 is a block diagram illustrating the construction of an integrity model, according to one embodiment of the invention.
  • the acquisition module is configured to acquire input parameter values including macroscopic kinematic parameter values, tool geometry parameters, cutting edge geometry parameters, section, tribology parameters (ie friction), and material parameters.
  • Input parameter values can be saved to the storage unit.
  • the parameters of the material include a specific heat capacity c cp , a density ⁇ and a Taylor-Quinney coefficient ⁇ .
  • the macroscopic kinematic parameters include a cutting speed parameter v c , a tooth feed parameter f z , an axial tool engagement parameter a p , and a radial engagement parameter of the tool has e .
  • the tool geometry parameters comprise a cutting angle ⁇ n , and a helix angle (ie edge obliquity) ⁇ s .
  • the tribology parameters include an average friction angle ⁇ a .
  • the microprocessor 5 is configured to construct the integrity model 21 using analytical and/or empirical physical relationships linking the set of input parameters to the set of output parameters.
  • the latter includes specific cutting coefficients representative of the cutting constraints.
  • the microprocessor 5 is configured to calculate, using geometric and/or empirical relations, the values of characteristic angles of the oblique cut comprising an oblique shear angle ⁇ i , a normal shear angle ⁇ n , a normal projection angle ⁇ n , an oblique projection angle ⁇ i and a chip flow angle ⁇ .
  • These values of characteristic angles of the oblique cut are calculated as a function of the values corresponding to the mean angle of friction ⁇ a , the angle of cut ⁇ n , and the helix angle ⁇ s . It will be noted that the characteristic angle values of the oblique cut make it possible to predict the forces and temperatures during the oblique cut.
  • the microprocessor is configured to determine the values of shear strain ⁇ s and strain rate d ⁇ s / dt in the primary shear band.
  • the microprocessor first uses the values of the cutting speed v c , the normal shear angle ⁇ n , the cutting angle ⁇ n and the undeformed chip thickness h to calculate by means of the analytical and empirical relationships the values of the parameters of the orthogonal cut comprising the values of the thickness of the shear band h s and of an asymmetry factor k s .
  • the microprocessor uses the values of thickness of the shear band h s and of the asymmetry factor k s calculated previously to determine a field of deformation and in particular, the values of shear deformation ⁇ s and of deformation rate d ⁇ s / dt in the primary shear band.
  • the coefficient q depends on the cutting speed and can vary between the values 3 and 7. For example q is equal to 3 for low cutting speeds and can reach 7 for high speeds.
  • the parameter ⁇ m represents the maximum strain rate
  • the parameter ⁇ is the normal shear angle ⁇ n deduced in block B5
  • the parameter ⁇ n is the cutting angle whose value is already known.
  • the microprocessor is configured to determine a shear stress ⁇ s in the primary shear band. For this, the microprocessor uses a law of behavior of the material (block B7) and the values of the parameters of the material comprising the specific heat capacity c cp , the density ⁇ and the Taylor-Quinney coefficient ⁇ as well as the values of shear strain ⁇ s and strain rate d ⁇ s / dt.
  • a constitutive law of the Calamaz and Coupard type can be used (described in “Strain field measurement in orthogonal machining of titanium alloy” Calamaz, Coupard, and Girot 2008). This law makes it possible to determine the shear stress ⁇ s in the primary shear zone as a function of the shear strain ⁇ s , the strain rate d ⁇ s / dt, the cutting angle ⁇ n , the melting temperature of the material T m , of the ambient temperature T r and of the temperature in the primary shear band T s .
  • the microprocessor uses the constitutive law as well as a differential equation defining the temperature in the primary shear band T s as a function of the shear stress ⁇ s to determine the temperature field T s and the stress of shear ⁇ s by a numerical integration.
  • the thermal conductivity is negligible and the thermal phenomena in the shear band evolve under adiabatic conditions, thus making it possible to cancel the term K ⁇ T (ie K ⁇ T ⁇ 0).
  • a thick chip (h>0.1mm) makes it possible to effectively evacuate the calories generated during the formation of the chip and makes it possible to lower the temperature on the machined surface.
  • increasing the cutting speed makes it possible to generate an adiabatic cut and lower the temperature on the machined surface.
  • the microprocessor is configured to calculate the specific cutting coefficients comprising a tangential edge force coefficient K tc , a radial edge force coefficient K rc , and an axial edge force coefficient K ac , as a function of shear stress ⁇ s , oblique shear angle ⁇ i , normal shear angle ⁇ n , normal projection angle ⁇ n , oblique projection angle ⁇ i and l helix angle ⁇ s .
  • the specific cutting coefficients are defined by the following equations: [Math.
  • K ct ⁇ s ⁇ cos ⁇ not + tan ⁇ I tan ⁇ s / cos ⁇ not + ⁇ not cos ⁇ I + tan ⁇ I sin ⁇ I sin ⁇ not [Math. 17]
  • K rc ⁇ s ⁇ sin ⁇ not / cos ⁇ not + ⁇ not cos ⁇ I + tan ⁇ I sin ⁇ I cos ⁇ s sin ⁇ not [Math.
  • K ac ⁇ s ⁇ tan ⁇ I ⁇ cos ⁇ not tan ⁇ s / cos ⁇ not + ⁇ not cos ⁇ I + tan ⁇ I sin ⁇ I sin ⁇ not
  • the values of these specific coefficients make it possible to predict the thermomechanical loading during the machining of a part.
  • microprocessor is configured to frame cutting parameters so that the values of the specific coefficients are included in an interval guaranteeing the integrity of the machined part.
  • the cutting parameters are easily measurable cutting operating parameters during machining, such as the power P or the torque C at the spindle of the machining machine or the electrical intensity circulating in the machining machine.
  • the microprocessor uses the integrity model to frame the cutting parameters so that the values of the specific output coefficients are representative of optimum material integrity of the workpiece.
  • the microprocessor is configured to calculate instantaneous machining forces comprising a tangential edge force F t , a radial edge force F r , and an axial edge force F ⁇ , by function of the specific cutting coefficients (tangential edge force coefficient K te , a radial edge force coefficient K re , an axial edge force coefficient K ae ) and a tooth width in engagement b ⁇ s (ie the contact length between the tooth and the surface) and the instantaneous undeformed chip thickness h.
  • These instantaneous machining forces are defined by the following expressions: [Math.
  • F you K ct ⁇ b ⁇ s ⁇ h + K you ⁇ b ⁇ s [Math. 20]
  • F r K rc ⁇ b ⁇ s ⁇ h + K D ⁇ b ⁇ s [Math. 21]
  • F at K ac ⁇ b ⁇ s ⁇ h + K ae ⁇ b ⁇ s
  • edge force coefficients Kte, Kre, and Kae are practically equal to zero since the edge sharpness radius r ⁇ tends towards 0 for a cutting tool that is new or in good condition.
  • operating parameters can be determined such as, for example, the intensity of the electric current circulating in the machining machine or the vibration at the level of the spindle.
  • the microprocessor is configured to establish fatigue reduction thresholds as a function of the corresponding operating parameters reporting a machining anomaly or a broken tool.
  • the acquisition module 3 is configured to acquire, at successive instants of machining, values of an operating signal (power, torque, electrical intensity, etc.) coming from the machining machine .
  • microprocessor 5 is configured to compare the value of the operating signal with the corresponding fatigue threshold in order to verify that the operating signal does not exceed the fatigue threshold, thus guaranteeing the material integrity of the machined part.
  • step E3 the microprocessor implements a numerical iteration defined below (see also block B5) to determine the parameters of the oblique cut:
  • step E11 the microprocessor determines the power at the spindle of the machining machine using equation (23).

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  • Engineering & Computer Science (AREA)
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  • General Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Manufacturing & Machinery (AREA)
  • Automation & Control Theory (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
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  • Computer Vision & Pattern Recognition (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
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EP21188642.9A 2020-09-29 2021-07-30 System zur bearbeitungskontrolle eines werkstücks Active EP3974104B1 (de)

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FR2009937A FR3114529A1 (fr) 2020-09-29 2020-09-29 Systeme de controle d’usinage d’une piece

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TWI702535B (zh) * 2019-11-15 2020-08-21 財團法人工業技術研究院 單向纖維複合材料切削力學模型建模裝置與建模方法
US11865716B2 (en) * 2021-01-06 2024-01-09 Machina Labs, Inc. Part forming using intelligent robotic system

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1522384A1 (de) * 2003-10-07 2005-04-13 Leonello Zaquini Vorrichtung zur Überwachung der Bearbeitung eines Werkstücks durch Messung der Schneidkräfte
US20080161959A1 (en) * 2006-12-01 2008-07-03 Jerard Robert B Method to measure tool wear from process model parameters
WO2015079164A1 (fr) * 2013-11-29 2015-06-04 Snecma Procédé et dispositif de détermination de l'usure d'une face de dépouille d'un outil de coupe
WO2019145515A2 (fr) * 2018-01-26 2019-08-01 Laser Engineering Applications Méthode pour la simulation d'usinages laser et dispositif d'usinage laser utilisant ladite méthode

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JP3231027B2 (ja) * 1999-09-10 2001-11-19 義昭 垣野 Ｎｃ工作機械の数値制御装置
US10261495B2 (en) * 2014-10-29 2019-04-16 Makino Milling Machine Co., Ltd. Controlling operation of a machining tool
JP6100747B2 (ja) * 2014-11-26 2017-03-22 ファナック株式会社 切削条件変更機能を有する工作機械を制御する制御装置
JP6740208B2 (ja) * 2017-12-27 2020-08-12 ファナック株式会社 切削条件検証装置

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1522384A1 (de) * 2003-10-07 2005-04-13 Leonello Zaquini Vorrichtung zur Überwachung der Bearbeitung eines Werkstücks durch Messung der Schneidkräfte
US20080161959A1 (en) * 2006-12-01 2008-07-03 Jerard Robert B Method to measure tool wear from process model parameters
WO2015079164A1 (fr) * 2013-11-29 2015-06-04 Snecma Procédé et dispositif de détermination de l'usure d'une face de dépouille d'un outil de coupe
WO2019145515A2 (fr) * 2018-01-26 2019-08-01 Laser Engineering Applications Méthode pour la simulation d'usinages laser et dispositif d'usinage laser utilisant ladite méthode

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EP3974104B1 (de) 2024-05-29
FR3114529A1 (fr) 2022-04-01
CN115016395A (zh) 2022-09-06

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